An interest point is a point in an image which is characterized as follows. An interest point has a clear and a well-defined position in an image space. An interest point has a high degree of repeatability (i.e., an interest point is likely to be detected in two images of an object, even though the images were taken in different conditions, such as by different cameras, resolutions, lighting conditions, and shooting angles). Interest points are employed for example, for image matching, object recognition, object categories in two dimensional images, three dimensional reconstruction, motion tracking and segmentation, robot localization, image panorama stitching and epipolar calibration. Interest point detectors are known in the art, and different detectors detect different features (i.e., Interest points) in an image.
U.S. Pat. No. 6,711,293 issued to Lowe, and entitled “Method and Apparatus for Identifying Scale Invariant Features in an Image and Use of Same for Locating an Object in an Image”, is directed to a method for identifying scale invariant features in an image. The method includes the procedures of producing a plurality of difference images, for each difference image locating a pixel amplitude extremum, for each amplitude extremum defining a pixel region around the amplitude extremum, for each pixel region dividing the pixel region into sub-regions, and for each sub-region producing a plurality of component descriptors.
The procedure of producing difference images involves successively blurring an input image to produce a blurred image, and subtracting the blurred image from an initial image, to produce the difference image. The collective set of component sub-region descriptors of each sub-region of the pixel amplitude extremum of a difference image, represents the scale invariant features of the original image.
U.S. Pat. No. 6,917,827 issued to Kienzle, and entitled “Enhanced Graphic Features for Computer Assisted Surgery System”, is directed to a system for inserting multiple guide pins into a bone. The system includes a probe, which has a graphic representation that includes a real probe tip portion and a virtual probe tip portion. The real probe tip portion of the representation correlates directly with the position of the real probe tip. The virtual probe tip portion of the representation correlates with a point in space that is located at a fixed and known relationship to the physical probe tip. In other words, whenever the physical probe is represented in an image, the virtual probe tip is also represented in that image. The location of the virtual tip probe within the image is determined according to the location of the probe representation. A surgeon positions the virtual probe representation on a bony landmark, in the body of a patient, in an x-ray image, for recording and calculating the position of the bony landmark.
U.S. Pat. No. 7,302,348 issued to Ghosh et al., and entitled “Method and System for Quantifying and Removing Spatial-Intensity Trends in Microarray Data”, is directed to a method for quantifying and correcting spatial-intensity trends in a microarray data. The method includes the procedure of employing a moving-window filter for selecting highest-signal-intensity features. In order to avoid overlooking features near the edge of the microarray boundary during moving-window filtering, the microarray features are extended symmetrically near the boundaries. The size of the symmetric extensions (i.e., of the near-boundary features) are determined by the size of the moving-window filter.